{"id":"W4306972075","doi":"10.1089/end.2022.0311","title":"Clinical Applications of Machine Learning for Urolithiasis and Benign Prostatic Hyperplasia: A Systematic Review","year":2022,"lang":"en","type":"review","venue":"Journal of Endourology","topic":"Kidney Stones and Urolithiasis Treatments","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; McGill University; Université de Montréal; McGill University Health Centre","funders":"","keywords":"Medicine; Checklist; Urology; MEDLINE; Hyperplasia; Systematic review; Data extraction; Algorithm; Artificial intelligence; Internal medicine; Computer science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002182191,0.0003338026,0.006169292,0.0003315069,0.00008880915,0.000006528007,0.0002109083,0.0002222545,0.00008171942],"category_scores_gemma":[0.003025601,0.0002164052,0.001340455,0.0002439392,0.0000954365,0.00003304093,0.00008022907,0.001039744,0.000002896672],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006606946,"about_ca_system_score_gemma":0.0005319505,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002636083,"about_ca_topic_score_gemma":3.318414e-7,"domain_scores_codex":[0.995159,0.0009154756,0.003095538,0.0002876085,0.0003047847,0.0002375846],"domain_scores_gemma":[0.9925589,0.002556652,0.004075517,0.0003491968,0.0002108665,0.0002488595],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001000884,0.0004050546,0.0004222397,0.8913172,0.00225462,0.0000690505,0.00002806742,2.105332e-7,8.944377e-8,0.0001786086,0.0002104535,0.1050143],"study_design_scores_gemma":[0.001556524,0.003231211,0.00001504119,0.08896641,0.03786093,0.01394733,0.00001728538,0.000009784479,4.805339e-8,0.00005178364,0.8542209,0.0001227676],"study_design_candidate":"systematic_review","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00001011628,0.9948871,0.0001254938,0.0003166869,0.0001315223,0.00435849,0.00006544338,0.000008607605,0.00009658714],"genre_scores_gemma":[0.00004136234,0.9968699,0.001316125,0.0004800244,0.0001435465,0.0007807607,0.00007490981,0.00006023181,0.0002331141],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.8540104,"threshold_uncertainty_score":0.882475,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06715869764492609,"score_gpt":0.4123458018330632,"score_spread":0.3451871041881371,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}